Barriers to adolescent and young men's access of reproductive health care

Purpose. The purpose of this study was to identify the health needs and barriers that young men face in accessing health care and family planning services and to identify what health centers can do to attract young men to the clinic. A focus group format was used to elicit ideas from participants. ^ Methods. Forty-eight young men participated in nine focus groups. The young men were asked about the health issues they have, the barriers they face in accessing reproductive health care, and what clinics can do to attract young men to the clinic. Thematic analysis principles were used to identify the main themes that emerged in the focus groups. ^ Results. Sexually transmitted infections (STIs), mental health problems, and drug use were the major health issues that were mentioned in the majority of the focus groups. The main barriers discussed in the focus groups were attitudinal factors such as young men thinking it is unmanly to seek help, emotional factors such as young men not seeking help because of their ego or pride, and institutional factors such as the location of the clinic. The main suggestions for improvements in the health clinic included decreasing waiting times, emphasizing the fact that the clinics are free for males, having more female nurses, and encouraging clinic staff to treat the young men with respect. Young men suggested advertising and promoting the clinic in schools, in the community, and through the media. Focus group participants also provided their input about the design and format of the clinic flyer. ^ Conclusions. Many studies focus on the reproductive health care needs of adolescent and young females. This study has helped to show that young men also have health care needs and face barriers to accessing reproductive health care services.^

Process to develop a State Model Law to reduce prescription drug trafficking while protecting pain management

This paper will discuss the intersection of pill mills and the under-treatment of pain, while addressing the unintended consequence that cracking down on pill mills actually has on medical professionals' treatment of legitimate pain in clinical settings. Moreover, the impact each issue has on the spectrum of related policy, regulatory issues and legislation will be analyzed while addressing the national impact on medical care. Lastly, this paper will outline a process to develop a State Model Law on this subject. This process will include suggestions for the future and how we can move forward to adequately address public safety needs and how we can attempt to mitigate the unintended impact prescription drug trafficking has had on a patient's right to appropriate pain management. This balance is achievable and this paper will address ways we can find this elusive balancing point through the development of a State Model Law. ^

Factors affecting prenatal care use and pregnancy outcome in Texas: A comparative study among and within Black, Anglo, and Hispanic populations

This research project is a study in the field of public health to test the relationships of demographic, socioeconomic, behavioral, and biological factors with (1) prenatal care use and (2) pregnancy outcome, measured by birth weight. It has been postulated that demographic, socioeconomic, and behavioral factors are associated with differences in the use of prenatal care services. It has also been postulated that differences in demographic, socioeconomic, behavioral, and biological factors result in differences in birth weight. This research attempts to test these two basic conceptual frameworks. At the same time, an attempt is made to determine the population groups and subgroups that are at increased risk (1) of using fewer prenatal care visits, and (2) of displaying a higher incidence of low birth weight babies. An understanding of these relationships of the demographic, socioeconomic, behavioral, and biological factors in the use of prenatal care visits and pregnancy outcome, measured by birth weight, will potentially offer guidance in the planning and policy development of maternal and child health services. The research considers four major components of maternal characteristics: (1) Demographic factors. Ethnicity, household size, maternal parity, and maternal age; (2) Socioeconomic factors. Maternal education, family income, maternal employment, health insurance coverage, and household dwelling; (3) Behavioral factors. Maternal smoking, attendance at child development classes, mother's first prenatal care visit, total number of prenatal care visits, and adequacy of care; and, (4) Biological factors. Maternal weight gain during pregnancy.^ The research considers 16 independent variables and two dependent variables.^ It was concluded that: (1) Generally, differences in demographic, socioeconomic, and behavioral factors were associated with differences in the average number of prenatal care visits between and within population groups and subgroups. The Hispanic mothers were the lowest users of prenatal care services. (2) In some cases, differences in demographic, socioeconomic, behavioral, and biological factors demonstrated differences in the average birth weight of infants between and within population groups and subgroups. (3) Differences in demographic, socioeconomic, behavioral, and biological factors resulted in differences in the rates of low birth weight babies between and within population groups and subgroups. The Black mothers delivered the highest incidence of low birth weight infants.^ These findings could provide guidance in the formulation of public health policies such as MCH services, an increase in the use of prenatal care services by prospective mothers, resulting in reduction of the incidence of low birth weight babies, and consequently aid in reducing the rates of infant mortality. ^

Access to oral care --- A systematic review of a continuing public health issue among older adults

Oral health is essential for the general well being of the individual and collectively for the health of the population. Oral health can be maintained by routine dental care and visits to dental professionals, but accessing professional dental care may be a continuing difficulty in vulnerable older adult population. Many older adults are not frequent users of dental care, though oral health is crucial to their well-being and overall health. Access to care is the timely use of personal health services to achieve the best possible health outcomes. ^ Objectives: The aims of this review are to (i) to analyze and elucidate the relationship between socio-economic disparities in gender, ethnicity, poverty status, education and the continuing public issue of access to oral care, (ii) to identify the underlying causes through which these factors can affect access to oral care. This review will provide a knowledgeable basis for development of interventions to provide adequate access to oral care in older adults and implementing policies to ensure access to oral care; through highlighting the various socio economic factors that affect access to oral care among older adults. ^ Methods: This paper used a purposeful review of literature on socioeconomic disparities in access to oral care among older adults. The references considered in this review included all the relevant articles, surveys and reports published in English language, since the year 1985 to 2010, in the United States. The articles selected were scrutinized for relevancy to the topic of access to oral care and which included discussions of the effects of gender, ethnicity, poverty status, educational status in accessing oral care. ^ Results: Evidence confirmed the continuing disparity in access to oral care among older adults. The possible links identified were gender inequality, ethnic differences, income levels and educational differences affecting access to oral care. The underlying causes linking these factors with access to oral care were established. ^ Conclusion: The analysis of the literature review findings supported the prevalence of disparities in gender, ethnicity, income and education with its possible links affecting access to oral care. The underlying causes helped to understand the reasons behind this growing issue of inaccessible oral care. Further research is needed to develop policies and target dental public health efforts towards specific problem areas ensuring equitable access to oral services and consequently, improve the health of older adults.^

Costs and quality of medication reconciliation practice in primary care clinics

Medication reconciliation, with the aim to resolve medication discrepancy, is one of the Joint Commission patient safety goals. Medication errors and adverse drug events that could result from medication discrepancy affect a large population. At least 1.5 million adverse drug events and $3.5 billion of financial burden yearly associated with medication errors could be prevented by interventions such as medication reconciliation. This research was conducted to answer the following research questions: (1a) What are the frequency range and type of measures used to report outpatient medication discrepancy? (1b) Which effective and efficient strategies for medication reconciliation in the outpatient setting have been reported? (2) What are the costs associated with medication reconciliation practice in primary care clinics? (3) What is the quality of medication reconciliation practice in primary care clinics? (4) Is medication reconciliation practice in primary care clinics cost-effective from the clinic perspective? Study designs used to answer these questions included a systematic review, cost analysis, quality assessments, and cost-effectiveness analysis. Data sources were published articles in the medical literature and data from a prospective workflow study, which included 150 patients and 1,238 medications. The systematic review confirmed that the prevalence of medication discrepancy was high in ambulatory care and higher in primary care settings. Effective strategies for medication reconciliation included the use of pharmacists, letters, a standardized practice approach, and partnership between providers and patients. Our cost analysis showed that costs associated with medication reconciliation practice were not substantially different between primary care clinics using or not using electronic medical records (EMR) ($0.95 per patient per medication in EMR clinics vs. $0.96 per patient per medication in non-EMR clinics, p=0.78). Even though medication reconciliation was frequently practiced (97-98%), the quality of such practice was poor (0-33% of process completeness measured by concordance of medication numbers and 29-33% of accuracy measured by concordance of medication names) and negatively (though not significantly) associated with medication regimen complexity. The incremental cost-effectiveness ratios for concordance of medication number per patient per medication and concordance of medication names per patient per medication were both 0.08, favoring EMR. Future studies including potential cost-savings from medication features of the EMR and potential benefits to minimize severity of harm to patients from medication discrepancy are warranted. ^

Gender disparities in utilization, unmet need and expenditure for mental health care

Objectives: To compare mental health care utilization regarding the source, types, and intensity of mental health services received, unmet need for services, and out of pocket cost among non-institutionalized psychologically distressed women and men. ^ Method: Cross-sectional data for 19,325 non-institutionalized mentally distressed adult respondents to the “The National Survey on Drug Use and Health” (NSDUH), for the years 2006 -2008, representing over twenty-nine millions U.S. adults was analyzed. To assess the relative odds for women compared to men, logistic regression analysis was used for source of service, for types of barriers, for unmet need and cost; zero inflated negative binomial regression for intensity of utilization; and ordinal logistic regression analysis for quantifying out-of-pocket expenditure. ^ Results: Overall, 43% of mentally distressed adults utilized a form of mental health treatment; representing 12.6 million U.S psychologically distressed adults. Females utilized more mental health care compared to males in the previous 12 months (OR: 1. 70; 95% CI: 1.54, 1.83). Similarly, females were 54% more likely to get help for psychological distress in an outpatient setting and females were associated with an increased probability of using medication for mental distress (OR: 1.72; 95% CI: 1.63, 1.98). Women were 1.25 times likelier to visit a mental health center (specialty care) than men. ^ Females were positively associated with unmet needs (OR: 1.50; 95% CI: 1.29, 1.75) after taking into account predisposing, enabling, and need (PEN) characteristics. Women with perceived unmet needs were 23% (OR: 0.77; 95% CI: 0.59, 0.99) less likely than men to report societal accommodation (stigma) as a barrier to mental health care. At any given cutoff point, women were 1.74 times likelier to be in the higher payment categories for inpatient out of pocket cost when other variables in the model are held constant. Conclusions: Women utilize more specialty mental healthcare, report more unmet need, and pay more inpatient out of pocket costs than men. These gender disparities exist even after controlling for predisposing, enabling, and need variables. Creating policies that not only provide mental health care access but also de-stigmatize mental illness will bring us one step closer to eliminating gender disparities in mental health care.^

Bayesian adaptive designs for drug combinations in early phase clinical trials

Treating patients with combined agents is a growing trend in cancer clinical trials. Evaluating the synergism of multiple drugs is often the primary motivation for such drug-combination studies. Focusing on the drug combination study in the early phase clinical trials, our research is composed of three parts: (1) We conduct a comprehensive comparison of four dose-finding designs in the two-dimensional toxicity probability space and propose using the Bayesian model averaging method to overcome the arbitrariness of the model specification and enhance the robustness of the design; (2) Motivated by a recent drug-combination trial at MD Anderson Cancer Center with a continuous-dose standard of care agent and a discrete-dose investigational agent, we propose a two-stage Bayesian adaptive dose-finding design based on an extended continual reassessment method; (3) By combining phase I and phase II clinical trials, we propose an extension of a single agent dose-finding design. We model the time-to-event toxicity and efficacy to direct dose finding in two-dimensional drug-combination studies. We conduct extensive simulation studies to examine the operating characteristics of the aforementioned designs and demonstrate the designs' good performances in various practical scenarios.^

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

The effects of adequacy and content of prenatal care on birth outcomes in a high -risk Missouri population

The purpose of this observational study was investigation of the relationship between quantitative adequacy of prenatal care, specific prenatal care content and pregnancy outcome in a high risk Missouri population. A sample of 1484 women from three Missouri regions known to have high rates of low birth weight, infant mortality, and inadequate prenatal care rates participated in structured post-partum interviews. Approximately one-half of the sample had received adequate prenatal care and the other half inadequate prenatal care as determined by an index utilized by the Missouri Department of Health.^ Prenatal care content was assessed by reports of prenatal education in six different areas: Diet, smoking, alcohol, drug, preterm labor counseling, and advice on when to call the health provider if preterm labor was suspected by the woman. Low birth weight, in both term and preterm infants, were the two birth outcomes examined. A variety of maternal socio-demographic variables were also considered.^ The results of this study suggest that specific educational content, delivered during prenatal care, may have lessen the risk of giving birth to a preterm-low birth weight infant. Prenatal education for recognition of preterm labor, and advice on when to call the health provider if preterm labor was suspected were found to be associated with a decreased risk of preterm delivery. Specific educational content was not, however, associated with risk of term-low weight birth nor was quantitative adequacy of care associated with the risk of either term- or preterm-low birth weight.^ These findings reinforce a body of literature which stresses the importance of appropriate prenatal care in preventing preterm low birth weight. Additionally, the findings suggest interventions that may be specifically effective for prematurity prevention. ^